For many businesses, especially large enterprises, contact centers are a key contributor to revenue and customer satisfaction. While “omni-channel” (voice, chat, email, social) is how many if not most contact centers operate, calls are the still the most critical element of their communications.
Preventing data loss for data in motion is a challenge that Cribl Stream Persistent Queues (PQ) can help prevent when the downstream Destination is unreachable. In this blog post, we’ll talk about how to configure and calculate PQ sizing to avoid disruption while the Destination is unreachable for a few minutes or a few hours. The example follows a real-world architecture, in which we have.
In the vast, mystical realm of the internet, where websites come to life and cat videos rule the land, there resides a hidden hero – Website Monitoring. Armed with lightning-fast reflexes and a vigilante’s keen eye, this unsung champion is the secret sauce to soaring traffic.
Feature management is an emerging set of tools and techniques for developing and testing software based around feature flags. It’s intended to increase productivity and performance, as well as improve software quality. Of course, you’ll also need to keep tabs on all those feature flags, so it only makes sense to pair feature management with observability for a more holistic view of your software development cycles.
This blog post was co-authored by Igor Shvartser, Senior Technical Product Manager at Amazon Timestream, and Michael Mandrus, Senior Software Engineer at Grafana Labs. Grafana Labs Senior Software Engineers Stephanie Hingtgen and Kevin Minehart also helped with the content.